31 results about "Proof of concept" patented technology

Collision detection and estimation from a monocular visual sensor is an important enabling technology for safe navigation of small or micro air vehicles in near earth flight. In this paper, we introduce a new approach called expansion segmentation, which simultaneously detects “collision danger regions” of significant positive divergence in inertial aided video, and estimates maximum likelihood time to collision (TTC) in a correspondenceless framework within the danger regions. This approach was motivated from a literature review which showed that existing approaches make strong assumptions about scene structure or camera motion, or pose collision detection without determining obstacle boundaries, both of which limit the operational envelope of a deployable system. Expansion segmentation is based on a new formulation of 6-DOF inertial aided TTC estimation, and a new derivation of a first order TTC uncertainty model due to subpixel quantization error and epipolar geometry uncertainty. Proof of concept results are shown in a custom designed urban flight simulator and on operational flight data from a small air vehicle.

A code search tool greatly reduces time, cost, and other resource expenditures associated with implementing a new application. The tool is a search, navigation and visualization tool that accepts high-level processing concepts as inputs to identify, rank, and return the code of relevant existing applications. A software developer may use the relevant applications to rapidly build prototypes, identify requirements, and develop new applications. The tool provides an efficient way to improve the reuse of application logic to realize the high-level processing concepts, and more efficiently deliver proof of concept.

A design and proof of concept of a new type of WLAN, complete with simulation and results from the simulation has been described. Each AP Node is implemented as a self-contained embedded OS unit, with all algorithms resident in its Operating system. The normal day-to-day functioning of the AP node is based entirely on resident control algorithms. Upgrades are possible through a simple secure communications interface supported by the OS kernel for each AP node. Benefits provided by a wireless network, as proposed in this invention, are that: it installs out of the box; the network is self-configuring; the network is redundant in that mesh network formalism is supported, ensuring multiple paths; load balancing is supported; there is no single point of failure; allows for decentralized execution; there is a central control; it is network application aware; there is application awareness; there is automatic channel allocation to manage and curtail RF interference, maximize non interference bandwidth and enable seamless roaming between adjoining wireless sub networks (BSS) and it supports the wireless equivalent for switching—for seamless roaming requirements.

This invention discloses a method for communications faster than the Nyquist rate (FTN) and faster than the Shannon rate which method is Quadrature Layered Modulation (QLM). QLM properties include scaling the data symbol pulses to maintain the same error rate performance for all rates. QLM alternatively considers the increase in the data symbol rate to be a layering of additional communications over the same link. The Shannon bound is a limit on the capacity of a communication link when transmitting data symbols at the Nyquist rate. QLM observes one can communicate at FTN to transmit more information than the Shannon rate since the Nyquist rate captures the information in a frequency band and does not constraint the information. These properties describe QLM and a separate math proof-of-concept is disclosed. Implementation and performance data demonstrate QLM can support communications data rates which are at least double the Shannon rate.

When interacting and talking with each other, humans are quite successful at conveying information and reacting appropriately. That is, they are able to interpret situational information which in most cases is only implicitly given. This ability is in stark contrast to most of the current state-of-the-art computer and telecommunications systems, which in large are unaware of this context information. Consequently, there has recently been great interest in making applications more context-aware so that they can adapt to different situations and be more receptive to user's needs.

The purpose of this project was to explore how one through examining different kinds of context information can find ways to automatically set a user's presence status. This presence status is useful as it allows for a person to decide whether it is appropriate to initiate communication or not. Further, it was the mission of this project to review how a policy-based approach could be use together with the mentioned aggregated presence status to increase user personalisation of communication. Finally, the project set out to show how one can model and implement such a context-aware system using Ericsson's service creation framework; ServiceFrame.

The project used a model-driven approach (MDA) in which most of the effort went into modelling the functionality of the system using formal UML2.0 models and then transform these into code using code generation tools and MDA viewpoints. During the modelling of the system, it was decided to examine user's context information and from this classify the user's aggregated presence status by utilising a supervised learning classifier. In a proof-of-concept solution, the probabilistic classifier, Naïve Bayes, proved to be an extremely fast and accurate classifier which should be considered as a strong option in any future implementations of the system. Personalisation of communications by design was achieved both through allowing completely personal classification rules, as well as through a policy approach. This policy approach consisted of letting a user construct a personal prioritising of his or hers terminals based on his or her aggregated presence status. It is suggested to expand this approach by also taking the group membership of the entity which requests the user information into account.

Using supervised learning makes sure the system is not to be solely dependent on any particular context data sensor but rather having the ability to adapt to an ever-changing environment. With the expected explosion of context sensors in areas such as ubiquitous computing [15], this ability to adapt will become increasingly important in future context-aware systems. In addition to this flexibility, the use of supervised learning also introduces the ability to classify completely unknown scenarios. This means that even if the classifier encounters a new scenario which is has never seen before, it tries to predict a status based on the underlying previous data. It stated that these predictions often have a high degree of accuracy with the right training data.

The system used the agent oriented architecture, which it is stated has a good support for personalisation as agents generally are used to represent entities in the real world (e.g. users). Through this approach, the system allows for a completely personal classification of a user's current context. By doing so, it is acknowledged that pre-defined rules does not fit everyone, but should be adapted to give each person a high degree of personalisation.

The invention discloses a method for realizing Android system vulnerability detection on the basis of a vulnerability poc (Proof of Concept). The method comprises the following steps that: establishing a vulnerability description file and a vulnerability library; developing an APP (Application) program; installing the APP program on a detected Android terminal; through an ADB (Android Debug Bridge), establishing a communication link with the APP program through a superior detection system; after the APP program receives a detection starting instruction, starting detection work; according to Android system information, loading a corresponding vulnerability detection unit list by the APP program; executing loaded vulnerability detection units one by one by a vulnerability detection engine, executing a detection task, and collecting a detection result; combining the detection result with the corresponding vulnerability description file by the vulnerability detection engine to generate a final detection report, and returning the final detection report to the superior detection system through the communication link; and deleting the APP program, carrying out disconnection, and finishing detection. By use of the method, the technical problems of low detection efficiency, incomplete detection contents and poor user operation experience in the prior art can be solved, and deficiencies in an existing scheme are made up.

A system comprising a platform configured for communicating with enterprise end-users and for allowing the enterprise end-users to perform proof-of-concept testing for startups which provide respective enterprises with software products to be evaluated by the respective enterprises, the platform including processor functionality configured to analyze available information on enterprise data and, accordingly, generate metadata characterizing the enterprise data; generate artificial enterprise data conforming to the metadata; analyze available information on enterprise APIs and, accordingly, generate metadata characterizing the enterprise APIs; and generate at least one artificial API conforming to that metadata.

The invention discloses a filling type remote bug PoC(proof of concept) writing method and a bug detection method. The detection method comprises steps as follows: 1), a plurality of PoC writing templates and a template analysis processing frame are created; 2), a user inputs test information of a target remote bug through the PoC writing templates, and the test information comprises parameters of a bug test HTTP (hypertext transfer protocol) request, a request address, a request method and a result judgment condition; 3), the template analysis processing frame is used for analyzing the PoC writing templates after being filled by the user so as to acquire information required for initiating the HTTP request, and then the HTTP request is generated and executed; 4), the template analysis processing frame judges whether content fed back through execution of the HTTP request contains the target remote bug according to the result judgment condition.

The invention provides a method and a device for generating POC (proof of concept) data. The method comprises the steps of acquiring an invoking path of a loophole code segment in a target program according to the loophole code segment which has a loophole in the codes of the target program; testing the target program according to the invoking path and input data; acquiring the corresponding input data when the target program has an abnormity, and taking the corresponding input data as the POC data. By adopting the embodiment of the invention, the POC data can be quickly constructed.

Emerging evidence indicates that diminished activity of the vasoprotective axis of the renin-angiotensin system, constituting angiotensin converting enzyme2 (ACE2) and its enzymatic product, angiotensin-(1-7) [Ang-(1-7)] contribute to pulmonary hypertension (PH). However, clinical success for long-term delivery of ACE2 or Ang-(1-7) would require stability and ease of administration to increase patient compliance. Chloroplast expression of therapeutic proteins enables their bioencapsulation within plant cells to protect from acids and gastric enzymes; fusion to a transmucosal carrier facilitates effective systemic absorption. Oral feeding of rats with bioencapsulated ACE2 or Ang-(1-7) attenuated monocrotaline (MCT)-induced increase in right ventricular systolic pressure, decreased pulmonary vessel wall thickness and improved right heart function in both prevention and reversal protocols. Furthermore, combination of ACE2 and Ang-(1-7) augmented the beneficial effects against cardio-pulmonary pathophysiology induced by MCT administration.

Experiments have also been performed which indicate that this approach is also suitable for the treatment or inhibition of experimental uveitis and autoimmune uveoretinitis These studies provide proof-of-concept for a novel low-cost oral ACE2 or Ang-(1-7) delivery system using transplastomic technology for pulmonary and ocular disease therapeutics.

A proof-of-concept (PoC) method comprising: on a networked platform, serving a population of enterprise end-users and a population of ISV end-users, on which PoCs are run, providing a PoC-defining user interface via which at least one enterprise end-user generates a definition of at least one PoC; and using a processor to automatically assess whether an individual machine learning model embodied in a body of code of an individual software product registered for an individual PoC, is suitable for the individual PoC as defined by the definition.

High-quality surface coatings, and techniques combining the atomic precision of molecular beam epitaxy and atomic layer deposition, to fabricate such high-quality surface coatings are provided. The coatings made in accordance with the techniques set forth by the invention are shown to be capable of forming silicon CCD detectors that demonstrate world record detector quantum efficiency (>50%) in the near and far ultraviolet (155 nm-300 nm). The surface engineering approaches used demonstrate the robustness of detector performance that is obtained by achieving atomic level precision at all steps in the coating fabrication process. As proof of concept, the characterization, materials, and exemplary devices produced are presented along with a comparison to other approaches.

Advances in technology and the availability of low cost sensors have led to an unprecedented growth in the volume of spatial data. Unfortunately, the time required to evaluate even simple spatial queries over large data sets greatly hampers the ability to interactively explore these data sets and extract actionable insights. While modern hardware (such as Graphics Processing Units or GPUs) are increasingly being used to speed up spatial queries, existing solutions have two important drawbacks: they are often tightly coupled to the specific query types they target, making it hard to adapt them for other queries; and since their design is based on CPU-based approaches, it can be difficult to effectively utilize all the benefits provided by the said hardware. To overcome these issues, spatial data are represented as geometric objects and a set of composable operators that operate over these objects are defined. The expressiveness of the proposed representation is demonstrated by realizing standard spatial queries as a composition of the proposed operators. To illustrate the performance gains that can be attained, a proof-of-concept GPU-based implementation focusing on a subset of the operators was built and evaluated.

Embodiments of the invention disclosed herein provide a method of participating in prepaid programs through retail systems without the need to first upgrade their POS capabilities to participate, and allow for a merchant (retailer) to participate in proof of concept programs to determine if prepaid is a viable solution for their retail business model.

Disclosed are a method for achieving ultrahigh spectral resolution and a photonic spectral processor, which is designed to carry out the method. The disclosed photonic spectral processor overcomes the current 0.8 GHz spectral resolution limitation. The new spectral processor uses a Fabry-Perot interferometer array located before the dispersive element of the system, thus significantly improving the spectral separation resolution, which is now limited by the full width at half maximum of the Fabry-Perot interferometer rather than the spectral resolution of the dispersive element spectral as is the current situation. A proof of concept experiment utilizing two Fabry-Perot interferometers and a diffractive optical grating with spectral resolution of 6.45 GHz achieving high spectral resolution of 577 MHz is described.

Optogenetic and chemogenetic actuators are critical for deconstructing the neural correlates of behavior. However, these tools have several drawbacks, including invasive modes of stimulation or slow on/off kinetics. These disadvantages have been overcome by synthesizing a magnetically sensitive actuator, Magneto, comprised of the cation channel, TRPV4, fused to the paramagnetic protein, ferritin. Magneto permits non-invasive magnetic control over neuronal activity by showing remote stimulation of cells using in vitro calcium imaging assays, electrophysiological recordings in brain slices, in vivo electrophysiological recordings in freely moving mice, and behavioral outputs in zebrafish and mice. As proof of concept, the first magnetogenetic control of the nervous system was demonstrated by using Magneto to delineate a causal role of striatal dopamine receptor 1 neurons in mediating reward behavior in mice. Together, our results present Magneto as a novel actuator capable of remotely controlling circuits associated with complex animal behaviors.